High fidelity adaptive mirror simulations with reduced order models.

Area of Science:

• Optical engineering
• Computational mechanics
• Astronomy instrumentation

Background:

• Numerical simulations are crucial for designing large adaptive mirrors in Extremely Large Telescopes (ELTs).
• Increasing telescope size and bandwidth necessitates modeling the entire system, including support structures, not just the mirror.
• Efficient simulations require reducing the size of dynamic models to manage computational resources.

Purpose of the Study:

• To present a framework for developing reduced-order structural models of large adaptive mirrors.
• To enable computationally efficient simulations for adaptive optics systems in ELTs.
• To analyze the feasibility of these reduced models for the Giant Magellan Telescope (GMT) prototype.

Main Methods:

• Developed a framework in collaboration with Microgate for creating reduced-order structural models.
• Integrated the reduced dynamic model with other system components for comprehensive simulations.
• Applied and analyzed the reduced models for Microgate's GMT adaptive mirror prototype.

Main Results:

• The developed framework successfully creates reduced-order structural models for adaptive mirrors.
• Simulations using the reduced models are computationally efficient, allowing for faster analysis.
• The reduced models are feasible for application to the GMT adaptive mirror prototype.

Conclusions:

• Reduced-order modeling is an effective preprocessing step for adaptive mirror control system simulations.
• This approach significantly improves the computational efficiency of simulating large adaptive optics systems.
• The framework is validated for its applicability to next-generation astronomical instruments like the GMT.